health impact assessment of active transportation: a...
TRANSCRIPT
Health impact assessment of active transportation: a systematic review
Project: Physical Activity through Sustainable Transport
Approaches (PASTA)
Natalie Mueller Centre for Research in Environmental Epidemiology (CREAL) Barcelona, Spain Supervisors: Prof. Mark Nieuwenhuijsen & Dr. David Rojas-Rueda April 14th, 2015
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PASTA project http://pastaproject.eu/home/ • Aims at studying how active transportation can lead to
a happier more physically active population while at the same time improving air quality
• Longitudinal study in 7 European cities 14,000 people reporting their transportation behavior and experiences
• WP4 development of state-of-the-art HIA tool to quantify health impacts of AT
• existing HIA models, PASTA survey, knowledge gaps identified in review
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Background
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Health Impact Assessment (HIA)
• HIA estimates (un)intended health benefits and risks of public policies in order to increase health gains and prevent harms (Mindell et al. 2003)
• Predictive rather than empirical research tool (Parry and Stevens, 2001)
• Mode shift to active transportation (walking, cycling, public transport and any other ‘active’ mode; AT) has potential to alter determinants of health, which underpins importance of HIA
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Background
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Health pathways associated with active transportation Physical activity Air pollution
Traffic noise
Traffic incidents
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Background
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Health benefits of active transportation
Evidence exists on AT health benefits Health benefits are believed to be greater than associated detrimental effects However, a systematic summary of quantified health benefits and risks of a mode shift to AT does not yet exist!
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Background
de Hartog et al. 2010
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Systematic review - Methods
• Review quantitative HIA studies of a mode shift to AT on grounds of associated health benefits and risks
• Database searches of MEDLINE, Web of Science and TRID • Eligibility criteria:
• Mode shift to AT • Quantitative HIA methodology • Quantitative change in health pathway exposure distribution • Quantitative change in health outcome
• Outcome: Benefit-risk or benefit-cost relationship
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Methods
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Flow chart of study search (Feb 2014 – Dec 2014)
30 HIA studies of a mode shift to AT with quantified health benefits and risks
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Methods
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Results
• 12 comparative risk assessments • 12 cost-benefit analyses • 4 benefit assessments • 2 risk assessments (traffic safety)
• Interventions that produced mode shift were ‘pull’ interventions (e.g.
bike-sharing system) or ‘push’ interventions (e.g. fuel price increase)
• Studies covered a range of populations partially stratified by age, sex, ethnicity and population density
7 studies
18 studies
5 studies
(1 study)
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Results
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Mode shift scenarios
Results
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Bike
Air Pollution Physical Activity Traffic Incidents
Mortality
Walk
Morbidity
Injuries
General population
Life expectancy
Work absence Medical costs
Noise
Active Traveler
DALYs
Fatalities
Monetization
Productivity loss
10 3
4 General population
28 17 21
(3)
(3)
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Results
Health pathways
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Bike
Air Pollution Physical Activity Traffic Incidents
Walk
Noise
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Results
28 17 21 (3)
HIA modeling assumptions
Dose-response function
•8 linear •7 HEAT (WHO) log-linear/ threshold •3 linear/ threshold •4 curvilinear baseline PA •6 RR categories
Dose-response function
•17 linear •1 log-linear (Delhi)
Dose-response function
•13 linear distance/ time •8 non-linear ‘safety in numbers’, traffic volume, modal split, conflict types, kinetic energies, speed, road, age, sex
Dose-response function
•3 linear traffic volume, cost-function for vehicle-km
Health Outcome All-cause mortality, CVD, Diabetes, Weight gain, Cancer, Falls, Mental health
Health Outcome All-cause mortality,
Respiratory disease, CVD, Cancer, Birth outcomes, Activity-
restriction, Productivity
Health Outcome Fatality, Injury
Health Outcome NA
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Bike
Air Pollution Physical Activity Traffic Incidents
Walk
General population
Noise
Active Traveler General population
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Results
28
7 14
14 6
3
27 studies estimated net benefits Benefit-risk/ benefit-cost ratios: (-2) – 360 (median=9) 3 studies estimated negative effects, but were distinctive: 2 studies on exclusively traffic safety (incident increase) 1 study compared health benefits to excessive intervention costs
Benefits > Risks
1
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Estimated health impact of a mode shift to AT
Mode shift to public transport and car passenger
‘High risk modes’ ; increase in single-mode incidents (slipping)
Reduced motorized traffic volume ‘safety in numbers’; safer modes
Reduced motorized traffic volume
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Results
Biggest benefits come from PA
Not possible if 1 health pathway, incomparable units, health impacts not untangled from environmental and economic impacts
Risk to active traveler minimal
Net health benefits of AT are substantial, irrespective of geographical context. Projected health gains by increases in PA levels exceed detrimental effects of traffic incidents and air pollution exposure!
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Intra-population benefit differences
• Older people (typically ≥45 years) estimated to benefit greater from AT than younger people • The benefits of physical activity are estimated to greater outweigh the detriments of traffic incidents and air pollution exposure due to increased risk for chronic disease
• Physical activity benefits are presumed to be long-term in nature and physical activity can reduce absolute risk for disease
development
• Inconclusive whether older people benefit differently from same physical activity exposure compared to younger people
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Discussion
Woodcock et al. 2014
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Intra-population benefit differences – traffic safety
Death and injury at younger ages translates into a larger burden of disease; delayed benefits from physical activity discourages AT for younger people
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Discussion
High injury risk setting: The proportional change in baseline mortality makes AT appear especially hazardous for younger people
Low injury risk settings: Younger people experience traffic safety gain
Edwards and Mason 2014
de Hartog et al. 2010
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Intra-population benefit differences
• Males estimated to benefit more than females from mode shift to AT
• Males comply less with physical activity recommendations at baseline (Olabarria et al. 2012)
• Sexes have distinctive chronic disease incidence risk (Woodcock et al. 2014)
• Males benefit more from reduced motorized traffic incident risk (especially switching to low risk modes of public transportation and car-passenger) (Dhondt et al., 2013)
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Discussion
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Intra-population benefit differences
• Disadvantaged ethnic sub-populations estimated to benefit more than general population (Lindsay et al., 2011)
• Pronounced benefits relate to increased chronic disease incidence (Fang et al., 2012; Lindsay et al., 2011)
Health Equity? • AT land-use improvements mostly found in high income areas (Aytur et al.,
2008). • High-income neighborhoods report more AT facilities, more traffic safety
and less crime (Sallis et al., 2011)
• Intrinsic motivations for AT engagement and intention-behavior relationships vary among different social classes (Conner et al., 2013)
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Discussion
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Uncertainties in HIA of AT
• HIA modeling assumptions vary across studies
• Benefit-risk/ cost ratios only indicator of magnitude of impact
• Risk estimates taken from elsewhere – comparability?
• Uncertainty about shapes of DRF
• Behavior change (intrinsic motivations)
• Longevity of AT health benefits (time-lags, immediate vs long-term)
• Effects on health equity
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Discussion
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Future HIA of AT
• Acute impacts of AT (quality of life, less back pain, mental well-being,
happiness)
• Integration of impacts of new domains such as noise, diet, social capital,
crime or productivity
• In-depth study of age, sex and social class effects
• Low and middle income settings
• Children
• Skates or e-bikes
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HIA is valuable to improve the understanding of the inter-relationship between transportation and health
Benefits of AT are substantial, irrespective of geographical context. Projected health gains by
increases in PA levels exceed detrimental effects of traffic incidents and air pollution exposure
Mark Nieuwenhuijsen David Rojas-Rueda Tom Cole-Hunter Audrey de Nazelle Evi Dons Regine Gerike Thomas Götschi Luc Int Panis Sonja Kahlmeier and the PASTA team and PASTA partners
Natalie Mueller CREAL Barcelona Biomedical Research Park (PRBB) Doctor Aiguader, 88 | 08003 Barcelona, SPAIN [email protected] | +34 93214 7314